1. Field of the Invention
The present invention is directed to methods of estimating protein-protein or protein-peptide binding affinities, and more particularly to methods of estimating protein-protein or protein-peptide binding affinities using free energy functions.
2. Description of the Related Art
A free energy function can be defined as any mathematical expression that relates macroscopic free energy changes to microscopic or molecular properties. Free energy functions can be used to explain and predict the affinity of a ligand for a protein and to score and discriminate between native and non-native binding modes. However, there is a natural tension between developing a function fast enough to solve the scoring problem but rigorous enough to explain and predict binding affinities.
There is a need for computational methods to explain and predict free energy changes for biophysical and biochemical processes (Ajay et al. (1995) J. Med. Chem. 38(26):4953-4967; Gilson et al., (1997) Biophys. J. 72(3):1047-1069; Guerois et al., (2002) J. Mol. Biol. 320(2):369-387; Vajda et al., (1997) Curr. Opin. Struct. Biol. 7(2):222-228). An important class of biophysical phenomena is that of non-covalent protein-protein interactions. Such vital activities as cellular growth, self-reproduction, and cellular communication are supported by a byzantine network of signaling cascades and metabolic pathways which rely on the coordinated and tightly regulated activities of interacting proteins, thus making protein-protein interactions attractive targets for therapeutic intervention (Feller et al., (2006) Curr. Pharm. Des. 12(5):529-548). The ability to estimate the free energy changes that control protein-protein associations will allow us to predict whether these interactions can occur under particular environmental conditions.
Specifically, free energy functions are needed to solve three problems: (1) predicting and explaining experimentally determinable protein-protein dissociation constants; (2) predicting and explaining how different mutations affect those equilibrium constants; and (3) accurately scoring and ranking the binding poses generated by protein-protein docking algorithms (Guerois et al., (2002) J. Mol. Biol. 320(2):369-387; Halperini et al., (2002) Proteins 47(4):409-443; Smith et al., (2002) Curr. Opin. Struct. Biol. 12(1):28-35; Weng et al., (1997) Protein Sci. 6(9):1976-1984). Ideally, the function should also be transferable; it should work equally well for a diverse and large number of proteins. Given the biological and clinical importance of free energy functions and the nature of the scientific challenge, a considerable amount of effort has been devoted to researching free energy methods (Ajay et al., supra; Guerois et al., supra; Horton et al., (1992) Protein Sci. 1(1):169-181; Jackson et al., (1988) J. Mol. Biol. 276(1):265-285; Krystek et al., (1993) J. Mol. Biol. 234(3):661-679; Ma et al., (2002) Protein Eng. 15(8):677-681; Rognan et al., J. Med. Chem. 42(22):4650-4658; Schapira et al., (1999) J. Mol. Recognit. 12(3):177-190; Vajda et al. supra; Weng et al., supra; Xu et al., (1997) J. Mol. Biol. 265(1):68-84; Zhang et al., (2005) J. Med. Chem. 48(7):2325-233; Zhou et al., (1998) Fold. Des. 3(6):513-522). Despite its importance, the development of a function to solve all three problems remains elusive. In part, this is because theoretical validity and physical meaningfulness tend to exclude computational efficiency (Gilson et al., supra; Rognan et al., (1999) J. Med. Chem. 42(22):4650-4658).
Computer-based modeling of interactions between molecular entities using various energy functions are the subject of several patents and patent applications as follows:
U.S. Pat. No. 6,970,790 discloses a method and apparatus for an analysis of molecular combinations featuring two or more molecular subsets, wherein either one or both molecular subsets are from a plurality of molecular subsets selected from a molecule library, based on computation of the electrostatic affinity of the system via utilization of a basis expansion representing charge density and electrostatic potential functions associated with the first and second molecular subsets in a coordinate system.
U.S. Pat. No. 6,823,267 discloses a computer-assisted method for creating and displaying a model of a molecule in which residues that are affected by the binding of a ligand to the molecule are highlighted, making it possible to trace the path of propagation of a binding signal through the molecule.
U.S. Pat. No. 6,741,937 discloses methods and systems of predicting binding affinity between a ligand and a receptor. In one embodiment, the predicted binding affinity (pKj) is determined by at least using a formulapKj=C0+C1*vdW+C2*Att—pol+C3*(Att—pol*Att—pol+Rep—pol*Rep—pol)where vdW represents the van der Waals interaction energy between the ligand and the receptor; Att_pol represents the surface area of the ligand forming complimentary polar interactions with the receptor; and Rep_pol represents the surface area of the ligand forming uncomplimentary polar interactions with the receptor.
U.S. Pat. No. 6,671,628 discloses methods which may be implemented in computer systems for screening a database of candidate molecules to determine whether any particular subset of candidate molecules may be docked to a target molecule. These methods determine the force field of a target molecule only once and may be used for screening a large number of candidate molecules.
U.S. Pat. No. 5,600,571 discloses a method for determining the most stable tertiary structure of a protein having a known primary structure which comprises the steps of (a) producing a reduced representation of the protein by assigning to the protein (i) all secondary structural motifs present therein and (ii) all φ and Φ dihedral angles for the amino acid residues present therein; (b) determining which conformations of the reduced representation are physically permissible, so as to determine which conformations of the protein are physically permissible; and (c) determining which of the physically permissible conformations of the protein possesses the lowest free energy, so as to thereby determine the most stable tertiary structure of the protein.
U.S. Patent Application Publication No. US 2007/0038379 discloses a hierarchical protocol using multiscale molecular dynamics and molecular modeling methods to predict the structure of G-Protein Coupled Receptors. The protocol features a combination of coarse grain sampling methods, such as hydrophobicity analysis, followed by coarse grain molecular dynamics and atomic level molecular dynamics, including accurate continuum solvation, to provide a fast and accurate procedure for predicting GPCR tertiary structure.
U.S. Patent Application Publication No. US 2006/0136139 discloses computational methods for identifying the protein receptors likely to bind a drug, which can provide accurate predictions of the drug's ability to bind to each homologue of the receptor using energy minimization functions.
U.S. Patent Application Publication No. 2005/0214788 discloses methods and systems for modeling molecular systems or other physical systems using scaling optimization. The disclosed method includes predicting a conformation of a ligand inside a binding site using a computer system by the steps of representing a candidate ligand by topological clusters, and scaling conformational and/or orientational degrees of freedom or their corresponding derivatives iteratively while applying one or more optimization and/or scoring and/or energy determination functions.
U.S. Patent Application Publication No. 2005/0123993 discloses methods for determining the affinity between polypeptide amino acid residues and one or more molecular fragments, and for using the affinity values to aid in drug design including a computer simulation which calculates the interaction energy between a polypeptide and at least one molecular fragment.
U.S. Patent Application Publication No. 2005/0119835 discloses a method and apparatus for analysis of molecular combinations featuring two or more molecular subsets. The computational method estimates the electrostatic affinity of the system via utilization of a basis expansion representing charge density and electrostatic potential functions associated with the first and second molecular subsets in a coordinate system. An electrostatic affinity, representing a correlation of the charge density and electrostatic potential functions of the first and second molecular subsets, is computed via suitable application of translation and rotation operators to the basis expansion coefficients over a sequence of different sampled configurations for the molecular combination.
In spite of the above technology, there is a need in the art for computational methods to explain and predict free energy changes for biophysical and biochemical processes. The present invention is believed to be an answer to that need.